What inspired this wish list request?
I encountered the situation when trying to realize classification with several Machine Learning algorithms on Mixture Space-Filling DoE data (presentation here : https://community.jmp.com/t5/Online-Abstracts/Synergy-Between-Design-of-Experiments-and-Machine-Lear...).
In order to present the results in a visual and clear way, I wanted to graph ternary plots with continuous responses expressing the change in classes, so I opted for the favorite class probability. But I had to do a workaround to actually create the graph, as the Ternary plot requires a formula column, so I did it in two steps :
- Create a classification model (SVM) and click on "Save Prediction formula". Class prediction is a formula column, but not the calculated probabilities columns for each class.
- Create a model with the same inputs variables / X's, but the response is the favorite class probabilities column. I can then save the probability formula and use it in the Ternary plot.
What is the improvement you would like to see? As in the model platform the calculation of the class probabilities is already done in order to predict the different classes, I would like to have the calculated class probabilities saved as formula columns in the datatable. This would be a more straightforward option, require less workarounds, and would avoid any model misspecifications in the second step.
Why is this idea important? Ternary plot or Surface Plot are essential tools to better visualize and apprehend RSM/Mixture models behaviors. With categorical responses/classes, it's difficult to represent correctly and continuously the variation in the experimental space, and I think using favorite class calculated probabilities formula could help enhance understand the influence and importance of factors on the categorical response(s).
